Medical training simulator including contact-less sensors

ABSTRACT

A medical training simulator includes contact-less sensors and corresponding detection objects, configured to enable sensor data collected during a training exercise to be used to evaluate the performance of the training exercise. The simulator includes a simulated anatomical structure, at least one contact-less sensor, and at least one detection object. During a training exercise, a spatial relationship between the contact-less sensor and the detection object produces data for evaluating performance of the training exercise. Either the contact-less sensor or the detection object is embedded in the simulated physiological structure, while the other is included in either a support for the simulated physiological structure, or as part of a tool used during the training exercise. Many types of contact-less sensors can be employed, including capacitance sensors, impedance sensors, inductive sensors, and magnetic sensors.

RELATED APPLICATIONS

This application is a continuation-in-part of a copending patentapplication, Ser. No. 10/718,492, filed on Nov. 20, 2003, which itselfis a continuation-in-part of a copending patent application Ser. No.09/695,380, filed on Oct. 23, 2000, the benefit of the filing dates ofwhich is hereby claimed under 35 U.S.C. § 120.

FIELD OF THE INVENTION

The present invention generally pertains to medical simulators for useas medical training aids, and more specifically, to medical simulatorsthat include contact-less sensors and corresponding detection objects,which facilitate the evaluation of a student's performance during atraining exercise implemented with the medical simulator.

BACKGROUND OF THE INVENTION

The use of simulated physiological structures for training medicalstudents and for providing skill training to practicing physicians iswidespread. Although cadavers have traditionally been beneficiallyemployed for this purpose, cadavers are not always readily available andare not well suited for all types of training.

Simulated physiological structures should preferably be usable multipletimes and should provide a realistic training experience correspondingto what the trainee would experience if performing a procedure on anactual patient. The need for such simulators is significant, becausethey can provide valuable training that will lead to more effectivetreatment of patients.

The use of a training model (such as a cadaver, an animal, or asimulator) is desirable to properly prepare a student or physician toperform procedures on a variety of patients. While anatomy followsgeneral rules, variations based on sex, age, height, and weight are thenorm. A surgical student should not just blindly follow directions suchas “make an incision four inches long and two inches deep, starting atthe navel.” Normal variations, such as the amount of body fat on aspecific patient, will significantly change the depth of fat tissue thatmust be incised to reach an internal organ. Surgeons must rely on theirknowledge of general anatomy, and evident cues (e.g., visually notingwhether the patient has a low or high percentage of body fat, or whetherthe patient is a child, an adult, a female, etc.) to determine thecorrect location and other variable parameters, before performing aprocedure on a specific patient. The use of cadavers, animal models, andanatomically correct simulators enable surgical students and physiciansto apply their knowledge of anatomy to develop experience in assessingthese factors, so as to properly determine the proper parameters to beapplied when executing a procedure on a live patient.

To provide the desired level of realism, a simulated physiologicalstructure used for training medical personnel should both tactilely andvisually resemble the anatomical structure being simulated. Even if asimulated physiological structure having simulated tissue faithfullyportrays finer details of an actual physiological structure and providesa realistic tactile sensation during a simulated procedure, the fewprior art simulators that may both tactilely and visually resemble theanatomical structure being simulated do not include means for producingobjective and measurable results that can be used to evaluate how well asimulated procedure is performed. Clearly, it would be desirable toemploy a simulated physiological structure that is able to provide arealistic tactile sensation during a simulated procedure, and which isalso able to provide an objective indication that can be used toevaluate how well a simulated procedure was executed.

SUMMARY OF THE INVENTION

In the present invention, contact-less sensors and correspondingdetection objects are used to enhance the performance of medicaltraining systems. By using contact-less sensors and correspondingdetection objects, each contact-less sensor and detection object can beincorporated into components of the medical training system in a waythat hides the sensors and detection objects from view. This approachnot only enhances a realistic appearance of the components of themedical training system, it also reduces a likelihood that any traineewill be able to infer a particular significance for any portion of acomponent of the medical training system by recognizing that a sensor ora detection object is disposed in a particular portion of the medicaltraining system. Many different types of contact-less sensors can beemployed, such as magnetic sensors, capacitance-based sensors, andinductive-based sensors.

In one embodiment, a medical model is configured to be used inconnection with a simulated or actual medical instrument. At least onesensor is incorporated into either the simulated instrument or themedical model. At least one detection object is incorporated into theother of the simulated instrument or the medical model. Each sensor islogically coupled to a processor, which is preferably implemented with apersonal computing device. The processor can be incorporated into themedical model or can be a stand alone unit. The detection objects arematched to the type of sensor employed. For example, if the sensor is areed switch or a Hall effect device, then the detection object will be amagnet.

Embodiments in which the detection object is incorporated into themedical model enable less-expensive medical models to be produced,because detection objects are generally less expensive than theircorresponding sensors. A single sensor integrated into a simulatedinstrument can detect a plurality of different detection objectsdistributed throughout a medical model. Furthermore, if the sensors areincluded in the simulated medical instrument rather than incorporatedinto the medical model, the medical model should not require wiring(which would complicate the manufacturing process of the medical model)to logically couple each sensor to the processor.

The location at which sensors or detection objects are incorporated intosimulated instruments and medical models is largely a function of aparticular exercise that will be performed using a specific simulatedinstrument and a specific medical model. For example, if a particulartraining exercise requires that a student identify a plurality ofdiscrete different features associated with the medical model, then adetection object (or sensor) can be disposed adjacent to each featurethat must be identified, such that the detection object (or sensor) ishidden from view. During the training exercise, when the studentproperly positions the simulated instrument adjacent to a feature to beidentified, a sensor (or detection object) incorporated into thesimulated instrument (for example at a distal end of the simulatedinstrument) is triggered, indicating that the student has correctlyidentified a particular feature.

In another embodiment, at least one detection object is incorporatedinto a disposable simulated physiological structure, such as a simulatedtissue. The detection object is incorporated into a portion of thesimulated tissue that must be dissected in a training exercise. Beforethe exercise, the simulated tissue is placed adjacent to a sensor bed,such that the sensor is triggered by the detection object in thesimulated tissue structure. When the student successfully dissects theportion of the simulated tissue structure incorporating the detectionobject, the sensor is no longer triggered by the detection object, andthe processor can provide feedback indicating that the student hassuccessfully completed the exercise. Such a sensor bed can bebeneficially incorporated into a box trainer. Further, it should beunderstood that the sensor bed can be used with the simulated tissue,and without a box trainer, if so desired. Additional detection objectscan be incorporated into the simulated tissue, with additional sensorsbeing incorporated into the sensor bed to facilitate proper positioningof the simulated tissue relative to the sensor bed.

The sensor data collected during a training exercise can be used toimmediately provide feedback to a student during the training exercise,or can be stored for later review, or the sensor data can be manipulatedto provide feedback only to a proctor monitoring the training exercise,so that the proctor knows whether the student has successfully completedthe training exercise. Sensor data (or feedback generated by theprocessor after receiving the sensor data) can be communicated to remotelocations over a network, so that the proctor and student do not need tobe in the second location. Thus, the present invention is well-suitedfor remote learning environments.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The foregoing aspects and many of the attendant advantages of thisinvention will become more readily appreciated as the same becomesbetter understood by reference to the following detailed description,when taken in conjunction with the accompanying drawings, wherein:

FIG. 1 schematically illustrates a medical model including a pluralityof contact-less sensors that are incorporated into the medical model,each sensor being configured to detect a detection object disposed on adistal end of a simulated medical instrument;

FIG. 2A is an enlarged view of a portion of the medical model of FIG. 1,illustrating an esophageal stricture substantially protruding into theesophagus;

FIG. 2B is an enlarged view of a portion of the medical model of FIG. 1,illustrating the esophageal stricture after a simulated dilationprocedure was performed so that the esophageal stricture generally nolonger protrudes into the esophagus;

FIG. 3 schematically illustrates a medical model including a pluralityof detection objects incorporated into the medical model, and aplurality of contact-less sensors disposed on a distal end of asimulated medical instrument, so that only certain detection objectstrigger specific sensors;

FIG. 4 schematically illustrates a medical model including a pluralityof detection objects incorporated into the medical model, and a singlecontact-less sensor disposed on a distal end of a simulated medicalinstrument, so that each detection object can be uniquely identified bythe sensor;

FIG. 5 schematically illustrates a medical model including a pluralityof capacitance-based sensors configured to detect a simulated medicalinstrument;

FIG. 6 schematically illustrates a medical model including a pluralityof evaluation circuits configured to receive a current induced by aninductor disposed on a distal end of a simulated medical instrument;

FIG. 7 schematically illustrates a medical model including platecapacitors disposed proximate a simulated esophagus, the platecapacitors being configured to detect a simulated medical instrumentbeing advanced into the simulated esophagus;

FIGS. 8A and 8B schematically illustrate a simulated joint incorporatingring shaped contact-less sensors configured to evaluate if a trainee hascorrectly positioned a syringe relative to the joint during anaspiration of the joint;

FIG. 9A schematically illustrates a box trainer including a sensor bedand a replaceable simulated physiological structure including detectionobjects;

FIG. 9B schematically illustrates the replaceable simulatedphysiological structure of FIG. 9B with a portion of the simulatedphysiological structure having been dissected, such that the sensor beddetects the dissection of that portion;

FIG. 10 schematically illustrates a medical training system includingcontact-less sensors coupled to a computing system to provide feedbackto a trainee during a simulated medical procedure or training exercise;

FIG. 11 schematically illustrates an exemplary configuration in which atraining system including contact-less sensors in accord with thepresent invention is coupled to a network, so sensor data and/orevaluation data relating to a training exercise obtained using thecontact-less sensors are transmitted to remote observers who are alsocoupled to the network;

FIG. 12 is a flowchart showing the sequence of logical steps employed toutilize contact-less sensors to collect data to be used to generate anevaluation of the performance of a training exercise or a simulatedmedical procedure; and

FIG. 13 schematically illustrates a medical training system includingcontact-less sensors coupled to a computing system to simulate anultrasound examination.

DESCRIPTION OF THE PREFERRED EMBODIMENT Overview of the PresentInvention

In the present invention, one or more sensors are incorporated into amedical training model that can be used for teaching and/or testing.Such sensors can be employed to provide feedback indicating how well asimulated procedure was performed using the medical training model. Eachmedical model preferably includes one or more simulated physiologicalstructures. Preferably, much of the model, and in particular thesimulated physiological structures, are formed out of elastomericmaterials to enhance a realism of the medical training model.

The sensors used in the present invention do not require physicalcontact between the sensor and an object that is to be detected and aretherefore referred to as “contact-less sensors.” In the context of thepresent invention, the object to be detected is generally a tool usedduring a simulated medical procedure (although in some embodiments, asensor is incorporated into such a tool, to detect objects incorporatedinto the model). Generally, the detection object or tool will be eitheran actual medical instrument, or a simulated medical instrument.Syringes, needles, scalpels, forceps, endoscopes, and laparoscopes arebut a few of the tools that might be employed in a simulated medicalprocedure. Employing sensors that can detect a tool without requiringthat there be actual physical contact between the tool and the sensorenables the sensors to be hidden from view. Hidden sensors arepreferable for at least two reasons. First, hidden sensors enable a morerealistic medical training model to be achieved (because a simulatedphysiological structure with clearly visible sensors would not lookrealistic); and second, if such sensors were visible to a student, thestudent might be able to identify a target location corresponding to asimulated medical procedure simply by noticing the sensors disposedadjacent to the target location.

The term “simulated medical procedure” is intended to encompass trainingactivities corresponding to actual medical procedures (e.g., anendoscopic examination of the upper gastrointestinal tract), as well astraining activities involving the use of the medical model, which do notcorrespond to any particular medical procedure. The term contact-lesssensor is intended to encompass all sensors that are capable ofdetecting the proximity of a detection object (such as the tooldescribed above) without requiring that there be physical contactbetween the sensor and the detection object.

Regardless of the sensor technology used, preferably, the sensor ispositioned sufficiently close to a portion of the medical model involvedin a specific simulated medical procedure, so that when a studentcorrectly uses the tool to perform the simulated medical procedure, thesensor will detect the presence of the tool.

Many different types of contact-less sensors are available. Thefollowing types of contact-less sensors are intended to be exemplary,rather than limiting on the scope of this invention. Magnetic sensors(including, but not limited to, reed switches), Hall effect sensors,impedance-based sensors (including but not limited to the use ofultra-wide band impedance sensors), capacitance-based sensors, and giantmagneto-resistive sensors can be employed for practicing the presentinvention. Combinations of infrared (IR) emitters and receivers can alsobe utilized. Factors relevant to the selection of a particular sensorinclude cost, range, sensitivity, and the preferred material of the toolor detection object to be detected.

Contact-less sensors can be separated into two broad categories,including analog sensors and digital sensors. Analog sensors provide asignal where, for example, the amplitude of the signal varies based on adistance between the sensor and the detection object. Digital sensors,like the reed switch noted above, function like on/off or binaryswitches. Selection of an analog sensor or a digital sensor is based inpart on how the sensor data are to be evaluated. For example, if aprecise 3-dimensional positioning determination is desired, a pluralityof analog sensors will be preferred (to enable positioning data to bedetermined using triangulation).

Certain sensor technologies require the use of a tool having a propertythat can be detected by the sensor. For example, some contact-lesssensor technologies rely on the sensor detecting a target object usingmagnetic properties (such as reed switches). Reed switches are digitalsensors that are triggered by the presence of a magnetic field ofsufficient strength. In embodiments that employ a reed switch as acontact-less sensor, the tool used to perform the simulated medicalprocedure (or the detection object placed in proximity of the sensorduring the procedure) must include a magnet capable of triggering thereed switch. If the simulated medical procedure requires the use of anactual or a simulated endoscope, a portion of such a tool can be formedfrom a magnetic material, or a magnet having a magnetic fieldsufficiently strong to trigger the reed switch can be incorporated intothe tool. The strength of the magnetic field required to trigger thereed switch will be a function of the sensitivity of the reed switch, aswell as the distance between the reed switch and the tool as it isemployed in a simulated medical procedure. If, in a particular medicalmodel, magnets cannot be used, then reed switches will be inappropriateand some other sensor technology must instead be used. Hall effectsensors detect the presence or the interruption of a magnetic field byproducing either a digital signal or an analog output proportional tothe magnetic field strength.

Capacitance-based sensors measure a change in capacitance, and thatchange is a function of a distance between a capacitor element and anobject (comprising another capacitance element) affecting the baselinecharge of the capacitor. Thus, capacitance-based sensors can be used asanalog sensors, although they are also often available as digital(on/off) sensors. For example, as a simulated instrument is broughtcloser to a capacitance sensor, the baseline capacitance of the sensorincreases. Capacitance sensors can therefore be used to determine therelative proximity between the sensor and an object and are thus usefulin enabling a medical training model to provide feedback about theproximity (and the degree of proximity) of an object relative to thesensor. To achieve a realistic model, such sensors will preferably beencapsulated or covered with a realistic elastomeric based simulatedtissue, to enhance the training experience. Capacitive sensors canrespond to all types of materials, and thus, can be used with tools thatare non-magnetic and non-metallic. The higher the dielectric constant ofthe target material, the greater the sensing range of the capacitivesensor.

Non-conductive detection objects can be used with impedance sensors.Both capacitance and impedance sensors can measure perturbations inspatially resolved, fringing electric fields. These fields are generatedby applying a voltage across precisely patterned metal electrodes. Asthe sensor is brought near the detection object (or vice-versa), theelectric field is altered. This small perturbation is measured as achange in capacitance or impedance by the sensor. In the case of acapacitance sensor, the sensor capacitance is decreased as it approachesa grounded detection object due to the effective shorting of some of itselectric field lines. In the case of an impedance sensor, penetration ofthe detection object by the sensor's electric fields enables a preciseresponse to the object's dielectric properties.

Inductive sensors are solid state sensors having three main components,including an oscillator, a triggering circuit, and a switchingamplifier. The oscillator generates a high-frequency electromagneticfield in the sensor's target area. When a metal (preferably a ferrousmetal) target enters the target area, eddy currents created in thetarget by the oscillator increase the load on the oscillator. When usedas a digital sensor, at a specific load, the trigger circuit senses thereduction in oscillation and signals the switching amplifier to changethe state of the sensor (e.g., “on” versus “off”). Inductive sensors canalso be configured as analog sensors, whose signal output varies basedon the distance between the metal target and the sensor. Inductivesensors detect metallic materials, and thus cannot be used with toolsthat are substantially non metallic.

While the use of sensors at plurality of different locations in amedical model is preferred (enabling more data points to be obtained,and facilitating more complex evaluations to be achieved), a singlesensor disposed proximate to a particularly critical location might bebeneficially employed. As noted above, a single sensor can beincorporated into the tool to be utilized, and detection objects can beincorporated into the medical model, which is useful where the sensorsare more expensive than the detection objects. This approach enables asimpler medical model to be achieved (only the sensor incorporated intothe tool needs to be logically coupled to a processor, as opposed to aplurality of sensors distributed throughout a medical model that must becoupled to a processor).

Sensors (or detection objects capable of triggering a sensor integratedinto a tool) that are incorporated into medical models and simulatedphysiological structures can be used in a variety of different ways.Three significant uses include collection of data, which are stored forlater use, collection of data to be processed to provide acontemporaneous feedback (such as a visual or an audible indication thata procedure has been performed correctly or incorrectly), which isprovided to a trainee, a proctor, or both, and collection of data thatare analyzed and may be used to trigger a simulated physiologicalresponse in the model or in the simulated physiological structure (e.g.,a change in a simulated heartbeat, a simulated muscular response, achange in a simulated respiratory rate, etc.—all of which can beeffected by controlling a servo or pump). In a relatively simpleimplementation, the sensor signal is used to provide a simple feedback,such as turning lights on or off, and/or the activation of aural,verbal, or textual prompts or cues. More complex sensor metrics involvedetermining a position of a simulated medical instrument (such as aneedle, a catheter, an endoscope, or other tool) during each phase of asimulated procedure. The sensor data can be manipulated and analyzed bya logical processing device, such as a computer. Using a computerenables sensor data to be immediately processed and displayed,immediately processed but stored for later use, stored for laterprocessing, compared to similar data, electronically distributed toother users in a network, or any combination thereof.

Instead of providing immediate feedback to a user, the feedback can behidden from the user, and instead made available to an instructor. Basedupon the feedback thus provided, the instructor may “grade” theperformance of the student. Such an application will be particularlyuseful in skill assessments of medical personnel in training or forproficiency certification.

Such sensors may not only be disposed at a target location at which asimulated medical procedure is to be performed, but they also can bedisposed at other portions of the medical model. For example, consider asimulated medical procedure in which a student is required to locate astomach tumor within a medical model (configured as a manikin) thatincludes a mouth, a throat, an esophagus and a stomach. The simulatedmedical procedure requires the student to introduce endoscopicinstruments into the stomach via the mouth. Sensors disposed proximateto the simulated stomach tumor will detect when a student has positioneda tool (such as a simulated or actual endoscope used to locate thestomach tumor) proximate the simulated stomach tumor, indicating thatthe student has correctly identified the stomach tumor. Other sensorscan be disposed in other portions of the stomach to detect that thestudent has not properly positioned the tool adjacent to the stomachtumor. A sensor disposed at the entrance of the mouth will detect whenthe student introduces the tool into the model, as well as detectingwhen the tool is withdrawn from the model (providing an elapsed time forthe entire simulated procedure). Sensors disposed adjacent to thebeginning and end of the esophagus can be used to determine the timerequired by the student to advance the tool through the esophagus.Sensors disposed throughout the stomach at locations other than at thestomach tumor can be used to determine the number of other sites in thestomach that the student examined before identifying the tumor.

The following describes several preferred surgical simulators (i.e.,medical models) incorporating contact-less sensors. It should beunderstood, however, that many other different medical models canbenefit from the incorporation of contact-less sensors, and thefollowing embodiments are intended to be exemplary, rather than limitingof the scope of the invention.

FIG. 1 schematically illustrates a medical model 10 that includes aplurality of contact-less sensors. It should be understood that simplermodels including fewer contact-less sensors (e.g., including a singularcontact-less sensor), as well as more complex medical models includingmore contact-less sensors can be achieved, as required. Thus, the numberof contact-less sensors illustrated in the following embodiments aremerely exemplary, rather than limiting of the scope of the presentinvention.

Medical model 10 includes a simulated esophagus 12 and a simulatedstomach 14. Preferably, these simulated anatomical structures are formedat least in part from elastomeric materials, such that a realistictraining model is achieved. Portions of the training model not beingutilized in training exercises need not be anatomically correct orrealistic in appearance. Esophagus 12 includes simulated abnormal tissue16 and an esophageal stricture 18, although it should be understood thatother medical conditions can also be readily simulated.

Abnormal tissue and esophageal stricture are commonly associated withgastroesophageal reflux disease (GERD), a very common disorder. GERDoccurs when the sphincter muscle at the bottom of the esophagus (notshown in FIG. 1) relaxes and regularly allows stomach acid into theesophagus. GERD is characterized by symptoms and/or tissue damageresulting from repeated or prolonged exposure of the lining of theesophagus to stomach acid. One type of tissue damage that can occur isreferred to as Barrett's esophagus, in which the normal tissue liningthe esophagus is replaced by tissue normally found in the stomach (i.e.,acid-resistant tissue). While the tissue replacement may be a defensemechanism, the presence of such abnormal tissue within the esophagus hasbeen clinically identified as being a risk factor for adenocarcinoma(cancer of the lower esophagus). Thus, abnormal tissue 16 is associatedwith Barrett's esophagus.

A second type of tissue damage associated with GERD is an esophagealstricture. The lower esophagus can open to the size of a quarter orwider. When recurrent inflammation occurs in the esophagus, scarringdevelops, underlying tissues becomes fibrous, and the opening narrows.In advanced cases, this narrowing, or stricture, can be severe. Theopening may be reduced to the size of a pencil or even smaller. Theprocessing of food and liquids are delayed, and they only move slowlyacross the opening into the stomach. A large piece of food, such as abite of meat, may completely block the esophagus. Thus, stricture 18 isalso associated with GERD.

Medical instruments may be inserted into the esophagus to performdiagnosis or treatment related to GERD. The medical instrument canprovide images to the physician, since the tissue associated withBarrett's esophagus is readily identifiable. The medical instrument mayalso be used to obtain a biopsy of abnormal tissue in the esophagus, todetermine if any of the abnormal tissue is cancerous. Medicalinstruments inserted in the esophagus can be used to dilate a stricture.One dilation technique involves positioning a deflated balloon withinthe stricture, and then inflating the balloon to dilate the opening.Simulated tool 26 can thus be configured to simulate an endoscope, atissue sampler, a dilator, or other medical instrument. If desired,stricture 18 can be formed using a fluid-filled bladder, so that thedilation forces fluid out of the bladder into a reservoir, enabling thestricture to be reduced in size. Fluid can then be forced from thereservoir back into the bladder, increasing the size of the stricture sothat the dilation procedure can be simulated repetitively. The dilationprocedure is similar to balloon angioplasty, and the same principles canbe employed to simulate balloon angioplasty in an appropriatelyconfigured simulated physiological structure. Medical model 10 can beused to train students in locating and identifying strictures andabnormal tissue associated with GERD. Sensors disposed proximatestricture 18 and abnormal tissue 16 can be used to determine if astudent has positioned an imaging tool immediately adjacent to suchstructures. Where stricture 18 is implemented as a fluid filled balloon,a contact-less sensor can be employed to determine if the structure isproperly dilated, as discussed in detail below, in connection with FIGS.2A and 2B.

As noted above, medical model 10 includes a simulated stomach tumor 20.A contact-less sensor disposed proximate stomach tumor 20 can be used todetermine if a student has positioned an imaging tool immediatelyadjacent to stomach tumor 20. Furthermore, a contact-less sensor can beused to determine if such a structure is properly removed, as discussedin detail below, in connection with FIGS. 9A and 9B.

Medical model 10 further includes a plurality of contact-less sensors 22a-22 h. Sensors 22 a-e are disposed at regular intervals along esophagus18. Sensor 22 f is disposed adjacent to abnormal tissue 16. Sensor 22 gis disposed at the junction of esophagus 12 and stomach 14. Sensor 22 his disposed adjacent a stomach tumor 20. Each contact-less sensor iscoupled to a processor 24 (as indicated by connector A), which can be aseparate component or integrated into medical model 10. A separateprocessor will reduce the cost and complexity of medical model 10.Ubiquitous personal computers can be used to implement the functions ofprocessor 24, or a dedicated processor can instead be employed. Theprocessor can be coupled with a display so that a trainee can receivefeedback during a simulated procedure (as shown in FIG. 10, as discussedin detail below), or the data collected by the contact-less sensors canbe provided only to a proctor and/or saved for later review. It shouldbe understood that each individual contact-less sensor is coupled toprocessor 24 so that the processor can track data from the individualsensors. While FIG. 1 schematically shows a cross section of medicalmodel 10, it should be understood that the contact-less sensors disposedadjacent to esophagus 12 can be disposed in a radial pattern aboutesophagus 12.

A distal end of simulated tool 26 includes a detection target 28,specifically selected to trigger the contact-less sensors selected. Inone embodiment, detection target 28 is a magnet, and each contact-lesssensor is either a Hall Effect sensor, a reed switch, or other magneticsensor. As those of ordinary skill in the art will recognize, reedswitches and many Hall Effect sensors are digital sensors. Digitalsensors can be employed to evaluate a trainee's performance in thefollowing manner.

In a hypothetical training exercise involving medical model 10, astudent is required to introduce tool 26 into esophagus 12. The studentis informed that medical model 10 includes an abnormality in one or moreof the esophagus and stomach. The evaluation of the student'sperformance includes determining whether the student correctly positionsthe tool at a location relevant to one or more abnormalities, and thelength of time it took the student to advance the tool through theesophagus and into the stomach. Detection target 28 is disposed on thedistal end of tool 26. Sensor 22 a is disposed at the beginning ofesophagus 12. When tool 26 is introduced into the esophagus, detectiontarget 28 will trigger sensor 22 a. A signal is sent from sensor 22 a toprocessor 24, enabling processor 24 to obtain a timing reference pointcorresponding to the point in time at which the student introduced tool26 into the esophagus. As detection target 28 passes by sensors 22 b, 22c, 22 d, and 22 e additional timing reference points are sent from thesensors to processor 24. FIG. 1 does not include any sensors disposedimmediately adjacent to stricture 18, although it should be understoodthat if desired, additional sensors can be placed adjacent to stricture18. Depending on the relative sizes of stricture 18 and tool 26, thestudent may be required to dilate stricture 18 in order to gain accessto stomach 14 (as discussed in detail below, in connection with FIGS. 2Aand 2B).

Sensor 22 g is disposed at the juncture between esophagus 12 and stomach14. As detection target 28 moves past sensor 22 h, a signal is sent toprocessor 24, providing a timing reference point corresponding to thepoint in time at which the student has successfully advanced tool 26through esophagus 12 into stomach 14. Thus, a potential metric withwhich the student's performance can be evaluated is the length of timeit took the student to successfully advance tool 26 through esophagusinto stomach 14 compared with the length of time required by a skilledpractitioner to complete the same action.

Sensor 22 f is disposed immediately adjacent to abnormal tissue 16.Preferably, sensor 22 f is calibrated such that if tool 26 is notdisposed immediately adjacent to abnormal tissue 16, but rather passesthrough esophagus 12 closer to sensor 22 g than sensor 22 f, sensor 22 fwill not be triggered. If sensor 22 g is triggered and sensor 22 f isnot triggered, it can be concluded that the student failed to locateabnormal tissue 16. Alternatively, the student can be instructed that ifany abnormal tissue or a tumor is located, the student should hold thetool immediately adjacent to the abnormal tissue or the tumor for aperiod of at least 30 seconds. Processor 24 can then be configured toevaluate the signal from sensor 22 f (or sensor 22 h) to determine ifthe sensor remains triggered for at least 30 seconds. If the sensor istriggered for less than 30 seconds, it will be concluded that thestudent passed the tool by the abnormal tissue or tumor, but failed torecognize the abnormal tissue or tumor. Failure to recognize an abnormaltissue or tumor will lower the student's score, and if desired, mayindicate that the student failed the training exercise.

In the training exercise described above, sensors 22 b-22 e, while eachproviding a timing reference point providing data relating to theposition of the tool within esophagus 12 at various times, are notspecifically required to determine the length of time required by thestudent to advance the tool through the esophagus into the stomach(sensor 22 a, disposed at the beginning of the esophagus, and sensors 22f and 22 g, disposed at the end of the esophagus, are sufficient forthat purpose) and could be eliminated if it is desired to reduce thecost and complexity of medical model 10.

As noted above, where stricture 18 is implemented as a fluid filledballoon, a contact-less sensor can be used to determine if the structureis properly dilated. A portion 30 of FIG. 1 corresponds to part ofstricture 18 and esophagus 12. Portion 30 is shown in an enlarged view,in FIGS. 2A and 2B. In FIG. 2A, stricture 18 protrudes significantlyinto esophagus 12. A sensor 22 i is incorporated into the wall ofesophagus 12, immediately behind stricture 18, which includes adetection object 32 (such as a magnet). Note that a reservoir 36 isempty. While not shown, it should be understood that a valve preventsfluid from stricture 18 from moving into reservoir 36, until a pressureis applied to stricture 18, thereby forcing fluid from stricture 18 intoreservoir 36 (thus enabling stricture 18 to be reduced in size). Asshown in FIG. 2A, the distance (as indicated by an arrow 34 a) betweendetection object 32 and sensor 22 i is sufficiently great, so thatsensor 22 i is not triggered.

In FIG. 2B, a tool such as a dilator has been used to apply pressure tostricture 18, forcing fluid from stricture 18 through the valve (notshown) into reservoir 36, so that stricture 18 is substantially reducedin size. Detection object 32 is now substantially closer to sensor 22 i,as indicated by an arrow 34 b, to trigger the sensor, which sends asignal to processor 24. The processor interprets the signal from sensor22 i as indicating that stricture 18 has been successfully dilated.While not separately shown, it should be understood that reservoir 36can be equipped with a piston (or some other mechanism known in the art)to force fluid to move from reservoir 36 back into stricture 18,expanding stricture 18, and thereby placing medical model 10 in acondition to be used by another student in another stricture dilationexercise.

Referring once again to the hypothetical training exercise discussedabove in connection with FIG. 1, detection target 28 was implemented asa magnet, and the contact-less sensors were implemented as magneticsensors (such as reed switches or Hall Effect sensors). It should benoted that a single magnetic sensor could be used in place of detectiontarget 28, and magnets could be used in place of sensors 22 a-22 h. Thesingle magnetic sensor on tool 26 would be coupled to processor 24, andeach time the magnetic sensor is tripped, the processor would be unableto determine which magnet (replacing sensors 22 a-22 h) caused thesensor to trip. Medical model 10 a of FIG. 3 can be used with a toolhaving a sensor, so that the sensors need not be included within themedical model. The processor can then specifically determine whichdetection target tripped the sensor (using the logic described below),reducing the complexity of the medical model (because the detectiontargets included in medical model 10 a need not be coupled to processor24), as well as reducing the cost of a medical simulator using medicalmodel 10 a and tool 26 a (because detection targets are generallycheaper than sensors, and fewer sensors are required). (Note thatelements common to FIG. 1 and the other Figures retain their numberingfrom one Figure to the next.)

Medical model 10 a of FIG. 3 is similar to medical model 10 of FIG. 1,and includes a simulated esophagus 12 and a simulated stomach 14.Magnets 40 a, 40 b, 40 c, and 40 d are also included. Magnet 40 a isdisposed at the beginning of esophagus 12, and magnets 40 b and 40 c aredisposed at the end of the esophagus, adjacent to the portion of themedical model where the esophagus joins with the stomach. Magnet 40 d isdisposed adjacent to stimulated stomach tumor 20. As noted above,processor 24 can be incorporated into medical model 10 a, or processor24 can be implemented as a separate device, such as part of a personalcomputer. A tool 26 a is used in connection with medical model 10 a andincludes sensors 38 a and 38 b disposed at the distal end of the tool.The sensors are logically coupled to processor 24. Preferably, sensors38 a and 38 b are implemented as reed switches, although it will beunderstood that other magnetic sensors could instead be used.Significantly, sensors 38 a and 38 b are configured to respond todifferent levels of magnetic fields. For example, as tool 26 a isintroduced into esophagus 12, sensors 38 a and 38 b will pass by magnet40 a. Magnet 40 a and sensors 38 a and 38 b have been selected so thatthe magnetic field produced by magnet 40 a is sufficient to triggersensor 38 a, but not sensor 38 b. Magnet 40 b has also had been selectedto have a magnetic field sufficient to trigger sensor 38 a (but notsensor 38 b), while magnet 40 c has been selected to have a magneticfield strength sufficient to trigger both sensor 38 a and sensor 38 b.Magnets 40 b and 40 c are disposed sufficiently far from each other sothat as tool 26 a is advanced through esophagus 12 and into stomach 14(so sensors 38 a and 38 b pass by magnets 40 b and 40 c), sensor 38 a istriggered twice, and sensor 38 b is triggered once. Magnet 40 d has beenselected to have a magnetic field strength sufficient to trigger bothsensor 38 a and sensor 38 b. Thus, if tool 26 a is properly positionedrelative to stomach tumor 20, sensor 38 a and sensor 38 b will each betriggered once.

The relative strengths of the magnets need to be selected based on thegeometry of the medical model. For example, the magnetic fields producedby magnets 40 a, 40 b and 40 c preferably should be capable oftriggering their corresponding sensors when tool 26 a is advanced intothe esophagus sufficiently to pass by one of the magnets, even if thetool is disposed near a portion of the wall of the esophagus that isopposite the portion of the wall behind which the magnets are disposed.If desired, ring shaped magnets encircling the esophagus can beemployed, or a plurality of individual magnets encircling the esophaguscan be employed, to ensure the magnetic field is distributed throughoutthe esophagus adjacent to the magnets/detection objects, so that thetool cannot pass by a detection object without triggering thecorresponding reed switch on the tool.

Processor 24 is therefore enabled to utilize the signals received fromsensors 38 a and 38 b to determine where tool 26 a is disposed withinmedical model 10 a. For example, when processor 24 receives one signalfrom sensor 38 a, and no sensor signal from sensor 38 b, processor 24 isable to determine that tool 26 a has just passed (or is disposedadjacent to) magnet 40 a. When processor 24 receives two signals fromsensor 38 a and one signal from sensor 38 b in close proximity to eachother, processor 24 is able to determine that tool 26 a has just passedby magnets 40 b and 40 c. When processor 24 receives one signal fromsensor 38 a and one signal from sensor 38 b simultaneously, processor 24is able to determine that tool 26 a has just passed by (or is disposedadjacent to) magnet 40 d.

Those of ordinary skill in the art will recognize that many differentcombinations of magnet strengths and magnet positions can be used toenable signals from sensors disposed on tools to be used to determinethe portion of a medical model which the tool has just passed, oradjacent to which the tool is currently disposed. Thus, medical model 10a is intended to be exemplary, rather than limiting of the scope of thisinvention.

The detection objects used in medical model 10 a require the use of atool having more than one sensor, to be able to detect the differentdetection objects. FIG. 4 illustrates a medical model 10 b that includesdetection objects, which are uniquely discriminable by a single sensor.Thus, a tool 26 b is required to include only a single sensor 42 on itsdistal end. Medical model 10 b includes a detection object 44 a disposedat the beginning of esophagus 12, a detection object 44 b disposed atthe juncture of esophagus 12 and stomach 14, and a detection object 44 cdisposed immediately adjacent to stomach tumor 20. Thus, medical model10 b is suitable for determining the time required by a student toadvance tool 26 b through the esophagus into the stomach, and also fordetermining whether the student is able to properly locate stomach tumor20. It should be understood that the location of detection objects inmedical model 10 b, and the specific training exercises discussed hereinare intended to be exemplary, rather than limiting of the scope of thisinvention.

It should also be understood that medical model 10 b and tool 26 b canbe implemented using different types of sensors and detection objects.For example, detection objects 44 a through 44 c can be implementedusing passive (i.e. short range) radiofrequency identification (RFID)tags, and sensor 42 can be implemented using an RFID tag reader. Thoseof ordinary skill in the art will recognize that RFID tags can beuniquely identified, and require no power (since all of the powerrequired by the RFID tag is obtained from the RFID tag reader, when theRFID tag reader interrogates the RFID tag).

Alternatively, detection objects 44 a-44 c can be implemented using barcodes (or other optically distinguishable markers), which may be visibleor non-visible to a user, and sensor 42 can be implemented with a singleoptical sensor capable of optically distinguishing different bar codes(or other forms of optical markings). Preferably, detection objects (andsensors) incorporated into medical models in accord with the presentinvention will be unobtrusive, such that their presence will not beapparent to the student. Invisible bar codes (i.e., bar codes made withinfrared reflective ink) have been developed, and can be used withouttheir presence being apparent to the student.

Digital and analog sensors have been discussed above. The reed switchesused for the sensors in medical model 10 a (FIG. 3) are digital sensors(i.e., they are either on or off). If sensor 42 is implemented using ananalog sensor, then such a sensor can discriminate between detectionobjects 44 a-44 c. For example, sensor 42 can be implemented using ananalog inductive sensor, configured to respond to masses of metal (thelarger the mass the larger the response). Thus, detection objects 44a-44 c could be implemented by different masses of the same type ofmetal, such that the inductive sensor is able to distinguish one massfrom another.

In yet another embodiment, detection objects 44 a-44 c can beimplemented using magnets having different magnetic field strengths,while sensor 42 is implemented as an analog Hall Effect sensor (or otheranalog magnetic sensor) that is capable of detecting the relativeintensities of the field produced by the magnets. In still anotherembodiment, detection objects 44 a-44 c can be implemented usingmaterials having different dielectric constants, such that the detectionobjects can be individually discriminated using an analog capacitancesensor (for sensor 42). For example, metal oxides have relatively highdielectric constants and can be readily discriminated from plastic andelastomeric materials that are used to construct medical model 10 b. Notonly will such metal oxides be readily discernible from the balance ofthe medical model, but the use of different metal oxides to implementeach different detection object should enable sensor 42 to discriminatebetween different detection objects. In particular, strontium titanateand titanium dioxide have relatively high dielectric constants andshould be usable in this invention.

Each of the embodiments discussed above in conjunction with FIG. 4 haveused detection objects that do not require a power supply in order forthe detection objects to be individually identifiable using acorresponding sensor. Implementing detection objects that require apower supply somewhat complicates the fabrication of medical model 10 b,because such detection objects need to be coupled to a power supply, orinclude a battery that will have a limited operational life. Where suchlimitations are acceptable, detection objects 44 a-44 c can beimplemented using IR transmitters, such that sensor 42 is implementedusing an IR transceiver able to individually distinguish detectionobjects 44 a-44 c. Those of ordinary skill in the art will readilyrecognize that such IR transmitters can be implemented in a veryunobtrusive manner, so as not to substantially reduce the realisticappearance of medical model 10 b or be noticeable by a user.

Turning now to FIG. 5, a medical model 10 c is illustrated that isconfigured to be used with a tool 26 c. Medical model 10 c includesabnormal tissue 16 disposed at the juncture between esophagus 12 andstomach 14, stomach tumor 20 disposed in stomach 14, and a stricture 18a (which has been dilated and does not substantially obstruct esophagus12). As with medical model 10 of FIG. 1, medical model 10 c includes aplurality of sensors that are incorporated into the medical model andwhich are logically coupled to processor 24. When a detection objecttriggers one of the sensors, a signal is sent to processor 24. Sensors23 a-23 h are implemented using capacitance-based sensors. Such sensorsrespond when an object is introduced into the space adjacent to thesensor, where such an object changes the dielectric constant of thespace. Thus, tool 26 c does not need to incorporate a detection objectat its distal end, because tool 26 c is the detection object. Asillustrated in FIG. 5, sensors 23 a, 23 b, and 23 c are triggered, andsensors 23 d-23 h have yet to be triggered.

FIG. 6 illustrates a medical model 10 d, including esophagus 12 andstomach 14, which is configured to be used with a tool 26 d thatincludes an inductor 46 disposed at its distal end. Medical model 10 dfurther includes a plurality of evaluation circuits 48. Each of theseevaluation circuits is logically coupled to processor 24. The functionof inductor 46 is to induce an electrical current inside each circuit 48adjacent to inductor 46. Electrical induction can be achieved using arotating magnet or an energized coil. While powerful and relativelysmall rare earth magnets (such as neodymium-iron-boron magnets) arereadily available, given the relatively small size of esophagus 12, itis more likely that inductor 46 will be implemented as an energizedcircuit (or electromagnetic coil). Once tool 26 d is inserted intoesophagus 12 and inductor 46 is energized, the position of the distalend of the simulated medical instrument (e.g., tool 26 d) can bedetermined by monitoring the plurality of evaluation circuits 48.Inductor 46 induces a current to flow in the evaluation circuits thatare close to the inductor. Those of ordinary skill in the art willrecognize that factors such as the distance from the inductor to theevaluation circuits and the design of the inductor will determine howmany of the evaluation circuits will experience an induced current andthat the amplitude of the current will depend upon the distance betweenthe tool and the evaluation circuits. As shown in FIG. 6, threeevaluation circuits 48 a, 48 b and 48 c on the right and threeevaluation circuits 48 d, 48 e and 48 f on the left are shown in bold,indicating that these evaluation circuits are experiencing an inducedcurrent. The evaluation circuits thus respond to the location ofinductor 46 without any physical contact by the simulated tool, andthus, each evaluation circuit functions as a contact-less sensor.Furthermore, because evaluation circuits 48 b and 48 e are disposedclosest to inductor 46, a greater current will be induced in evaluationcircuits 48 b and 48 e than in evaluation circuits 48 a, 48 c, 48 d and48 f. Feedback provided by the evaluation circuits in medical model 10 dis therefore based not only on the presence of an induced current, butalso on the magnitude of the induced current. This embodiment is incontrast to the sensor/detection object combinations discussed above,many of which provide feedback solely based on whether the sensor is inan on or off state (e.g. a binary digital response as opposed to ananalog response).

By monitoring the magnitude of the electrical currents flowing in theevaluation circuits, the evaluation circuits can be used to determinethe position of the distal end of tool 26 d. As a result, medical model10 d can be used to provide feedback about several different simulatedesophageal procedures. In a simulated diagnostic procedure, feedback canbe provided when, or if, the trainee properly positions an endoscopeadjacent to simulated abnormal tissue 16. In a simulated biopsy,feedback can be provided when, or if, the trainee properly positions atissue sampler to obtain a sample of simulated abnormal tissue 16, asopposed to normal esophageal tissue. In a simulated dilation procedure,feedback can be provided to determine if the trainee has properlypositioned the dilator to expand stricture 18 a. As noted above, othersensors can be used to determine if a fluid filled stricture has beenproperly dilated.

FIG. 7 illustrates a medical model 10 e, which includes acapacitance-based evaluation circuit configured in a significantlydifferent orientation. In medical model 10 e opposite sides of esophagus12 are configured as opposed plates 50 a and 50 b of a capacitor, andthe air in the esophagus is the dielectric between the opposed plates.When tool 26 d is introduced into the gap between the opposed plates ofthis capacitor (i.e., into the dielectric), the baseline charge of thecapacitor changes. This effect can be used to determine the location ofthe distal end of a simulated medical instrument (e.g., tool 26 d)relative to the esophagus. Such a capacitance sensing circuit islogically coupled to processor 24. While not specifically shown, itshould be understood that medical model 10 e can beneficiallyincorporate elements such as abnormal tissue, strictures, and tumors asshown in other medical model discussed above. In yet another embodiment,one wall of esophagus 12 (e.g., plate 50 a) can be configured as a firstplate of a capacitor, while simulated tool 26 d serves as the secondplate of the capacitor (in this embodiment, plate 50 b is not required).As the position of simulated tool 26 d changes relative to the portionof the esophagus configured as the plate of the capacitor, the baselinecharge of the capacitor changes and is measured.

While all of the medical models illustrated in the preceding Figures anddiscussed in detail above have generally corresponded to a torso andrelated internal body cavities of a human, it should be understood thatthe present invention is not limited to application only in such medicalmodels, but can also be implemented in many other different types ofmedical models, simulating many different type of anatomical structures.FIGS. 8A and 8B schematically illustrate how contact-lesssensors/detection objects are used in regard to a simulated knee 52 anda tool 54. It should be understood that other joints can be simulated,and the present invention is not intended to be limited in applicationonly to simulated knees. A common medical procedure performed on jointsis aspirating accumulated liquid from the interior of the joint. Thisprocedure is schematically illustrated in FIG. 8A, which shows theneedle of tool 54 (a syringe) being inserted into simulated knee 52.Simulated knee 52 accurately represents an actual knee and the tissueadjacent thereto. Elastomers are used to simulate tissues such as skin,muscle, and fat. More rigid polymers can be employed to simulate bone,cartilage, tendons and/or the ligaments associated with the knee.Simulated knee 52 includes sensors 56 a-56 d configured to evaluateaspiration of the simulated knee. It should be understood that otherjoint-related procedures can also be simulated, and sensorconfigurations can be specifically provided to evaluate a specificprocedure on such a joint. Thus, the present invention is not intendedto be limited to evaluating aspiration of joints.

Sensor 56 a is disposed adjacent to a skin layer of simulated knee 52,to determine if a person doing the procedure has selected the properposition for insertion of tool 54. As illustrated, sensor 56 a is a ringshaped sensor, which is triggered when tool 54 is inserted generallyinto the center of the annulus defined by ring sensor 56 a. While notspecifically shown, it should be understood that each sensor in FIGS. 8Aand 8B is logically coupled to a processor as discussed above.Inductance-based ring sensors are available from various manufacturersand respond to the proximity of metals. Therefore tool 54, specificallythe needle portion of the syringe, is preferably formed of a metalmaterial. Where ring sensor 56 a is implemented as a digital sensor,triggering the sensor will only indicate that the tool has been insertedgenerally into the center of the annulus defined by the ring sensor,thereby enabling a pass/fail grade to be provided regarding insertionlocation of tool 54. When ring sensor 56 a is implemented as an analogsensor, the processor can determine into what portion of the centralregion defined by the annulus of the ring sensor that tool 54 has beeninserted, enabling the processor to provide a higher grade forinsertions located closer to the center than an insertion that isoff-center within the annulus defined by ring sensor 56 a.

FIG. 8B schematically illustrates ring sensors 56 b, 56 c and 56 d,which are configured to monitor a depth to which tool 54 is insertedinto knee 52. Sensors 56 b, 56 c and 56 d are thus configured todetermine if the needle of the syringe has been inserted into knee 52along a desired track, and to an appropriate depth. As noted above, ifthe sensors are digital sensors, then the resulting evaluation willgenerally be a pass or fail grade. However, if the sensors are analogsensors, then a more quantitative grade can be provided based on howclose to the center of each sensor the needle is inserted and based uponthe relative depth (compared to the ideal depth) to which the needle isinserted.

FIGS. 9A and 9B schematically illustrate a box trainer and a simulatedtissue structure incorporating the detection objects and contact-lesssensors discussed above. Box trainers are often used to develop skillsrequired for endoscopic and laparoscopic surgery. The box, which can beopen or closed, simply provides a working space simulating an internaloperating site. The exercise object, such as a simulated tissuestructure, is inserted into the working area defined by the box.Endoscopic instruments are inserted into the working area to manipulatethe exercise object. In open box trainers, such manipulation occurswhile the student is looking directly at the simulated tissue structure.Some trainers use a system of mirrors to provide an image of theexercise object to the trainee, so that the trainee is not lookingdirectly at the exercise object. Still other box trainers incorporateimaging devices, so that the trainee views an image of the exerciseobject on a display while the exercise object is being manipulated. Boxtrainer 60 as shown in FIGS. 9A and 9B can comprise any of theabove-described types of box trainers. A sensor bed 64 is incorporatedinto a base 62 of box trainer 60. Preferably sensor bed 64 includes aplurality of sensors, although a basic embodiment may include only asingle sensor. Because the exercise objects are generally considered tobe disposable items, for cost considerations, it is preferred for thesensor to be part of the sensor bed/box trainer, which is usedrepeatedly. Generally, detection objects that can be detected by asensor are cheaper than the sensors themselves, and it is preferable totreat a detection object as a disposable item rather than treatingsensors as disposable items. Note that sensor bed 64 can be permanentlyincorporated into box trainer 60, or sensor bed 64 can be removablyattached to box trainer 60 such that a different sensor bed,specifically configured to detect different exercise objects, can beintroduced into box trainer 60 as required. Furthermore, while boxtrainers are useful training tools, such a sensor bed could be usedindependently of a box trainer. A sensor bed configured to be usedindependently of a box trainer will include one or more contact-lesssensors, and will be configured to support an exercise object. Such astand alone sensor pad may be larger than the exercise object, orsubstantially the same size as the exercise object (stand alone sensorpads of the same size as the sensor object will facilitate properpositioning of the exercise object to the sensor pad/sensor bed). Whilenot shown, it should be understood that each sensor is logically coupledto a processor as described above. Preferably, the sensor pad willinclude one or more data ports (such as a parallel port or a universalserial bus (USB) port) enabling the sensor pad to be coupled to acomputing system (wherein the computing system includes the processordescribed above).

As shown in FIGS. 9A and 9B, sensor bed 64 is incorporated into aportion of base 62. It should be understood that some exercise objectscan generally be as large as base 62, and in such cases, sensor bed 64would be sized accordingly.

Simulated tissue structure 66 includes features 68, 70, and 72; anddetection objects 74, 76, and 78. As discussed in detail above, thedetection objects are selected based on the type of sensor included insensor bed 64. In one embodiment, sensors 80, 82 and 84 in sensor bed 64are implemented using magnetic sensors; such as reed switches or HallEffect sensors. Detection objects 74, 76 and 78 can then be implementedusing magnets of appropriate magnetic field strengths, such that whensimulated tissue structure 66 is positioned properly relative to sensorbed 64, sensors 80, 82, and 84 are triggered. It should be understoodthat the magnetic sensors and magnets noted above are not the only typesof detection objects and sensors that can be implemented in exerciseobjects and sensor pads. Other types of detection objects and sensorsgenerally consistent with those discussed above can also be employed.

For sensor bed 64 and simulated tissue structure 66 to functionproperly, simulated tissue structure 66 needs to be accuratelypositioned relative to sensor bed 64. Several techniques can be used toenable such accurate positioning. In one embodiment, sensor bed 64 isvisually distinguishable from the rest of base 62. For example, ifsimulated tissue structure is 3 inches square, an appropriate sensor bedwould also be about 3 inches square. Sensor bed 64 can be formed from adifferent color plastic than the rest of base 62, so that a trainee canreadily identify on what portion of base 62 the simulated tissuestructure needs to be positioned. Furthermore, one or more of thesensors in sensor bed 64 can be configured to detect a correspondingdetection object in simulated tissue structure 66, such that when thesimulated tissue structure is properly positioned relative to sensor bed64, an audible or visual feedback is provided to the trainee to indicatethat the simulated tissue structure is properly positioned. For example,detection objects 74 and 76 are disposed at opposed edges of simulatedtissue structure 66. Sensor bed 64 includes a sensor 80 and a sensor 84.When simulated tissue structure 66 is properly positioned, sensor 80 istriggered by detection object 74, and sensor 84 is triggered bydetection object 76. If digital sensors are employed, some degree ofmisalignment may still result in the feedback being provided to thetrainee that the simulated tissue structure is properly positioned. Ifanalog sensors are implemented, more quantitative feedback can beprovided to the trainee, until the simulated tissue structure is moreprecisely positioned (e.g., the more accurately positioned the simulatedtissue structure is, the greater will be the magnitude of the signalsprovided by sensors 80 and 84).

Simulated tissue structure 66 is useful in the following exercise. Thetrainee is provided box trainer 60 and simulated tissue structure 66, asshown in FIG. 9A, is informed that one of features 68, 70, and 72corresponds to a disease condition, and that the diseased tissue must beremoved. Some aspect of feature 72, such as shape, color, or size willindicate to the student that feature 72 corresponds to the diseasedtissue. The student will use endoscopic instruments 86 to dissectfeature 72. Note that in this example, only feature 72 (whichcorresponds to the disease condition) includes a detection object. Withfeature 72 remaining attached to simulated tissue structure 66, sensor82 is triggered by detection object 78. When the student successfullyidentifies feature 72 as being diseased tissue and correctly dissectsfeature 72 as shown in FIG. 9B, sensor 82 will no longer be triggered bydetection object 78, and the processor can provide feedback to thestudent (or to a proctor) that the exercise was successfully completed.If however, the student incorrectly identifies feature 68 (or feature70) as corresponding to the disease condition, and dissects feature 68(or feature 70), the processor will determine that sensor 82 continuesto be triggered by detection object 78, and that the student has failedthe exercise. It should be understood that in this exercise, sensor bed64, and simulated tissue structure 66 are merely exemplary, and are notintended to be limiting of the present invention. Those of ordinaryskill in the art will readily recognize that many differentconfigurations of sensor beds, detection objects incorporated intoexercise objects such as simulated tissue structures, and exercises canbe provided, consistent with the above description.

Note that the box trainer and exercise object described above togetherdefine a medical model that includes both detection objects andcontact-less sensors. The other medical models described above includean esophagus and stomach (i.e., medical models 10, 10 a, 10 b, 10 c, 10d, and 10 e) and each required the use of a specific tool, where eithera sensor or detection object was incorporated into the tool (or the toolitself was the detection object). The endoscopic tools discussed abovein connection with the box trainer of FIGS. 9A and 9B are not requiredto include sensors or detection objects (although they optionally can),because the sensors are disposed in the sensor bed, and the detectionobjects are part of the simulated tissue structure (i.e., the exerciseobject).

FIG. 10 schematically illustrates one type of feedback that might beprovided to a student using a trainer including contact-less sensors andcorresponding detection objects in accord with the present invention. Asshown in this Figure, a student is performing a training exercise usinga trainer 85, which includes one or more contact-less sensors. Aprocessor coupled to the sensors (as described above) is further coupledto a display 87. Based on the student's performance as measured by thesensors, the processor causes one or more messages to be displayed tothe student. For example, a message 89 informs the student that the toolhas not been advanced deep enough into the trainer. A message 91 informsthe student that the tool has been inserted into the correct location.It should be understood that such messages are merely exemplary and arenot intended to limit the scope of the present invention. As notedabove, in some embodiments, no feedback will be provided to the studentduring the exercise. Instead, the feedback will be stored for laterreview and/or concurrently displayed to a proctor responsible forevaluating the student's performance during the exercise.

FIG. 11 schematically shows an exemplary configuration 100 in which atraining system 102 is connected to a network 104 to share datacollected during a training exercise, with remote observers 106 and 108,and optionally, with a remote instructor 110. It should be understoodthat the number of observers and instructors connected to network 104can readily vary. Training system 102 can, for example, be based on anyof the medical models discussed above, including those that simulate ahuman torso (i.e., models 10, 10 a, 10 b, 10 c, 10 d, and 10 e), as wellas medical models that are based on a sensor bed combined with one ormore exercise objects. In addition to a medical trainer including acombination of contact-less sensors and detection objects (a sensor bedcombined with an exercise object), or a medical model and tool includinga combination of contact-less sensors and detection objects (medicalmodels 10, 10 a, 10 b, 10 c, 10 d, and 10 e), system 102 includes acomputing device that is coupled to the network. The computing devicereceives sensor data (i.e., the computing device includes processor 24,as described above). If desired, the computing device can providefeedback via a display to the student during the training exercise (asdescribed above in connection with FIG. 10). Sensor data (and/or anevaluation of the training exercise) can also be streamed to other usersover network 104, which can be a private network used by a school ortraining facility, or a public network, such as the Internet. Such datacan be provided to other students, or to a proctor who will evaluate thestudent's performance based on the data/feedback received via thenetwork. The sensor data captured by the contact-less sensors can bestored in digital form, for example, on a hard drive (not separatelyshown) of the computing device of training system 102. If desired, thetraining system can also couple to a remote storage device 112 vianetwork 104, to store the sensor data (or an evaluation based on thesensor data) remotely. Such remote storage is particularly useful in ascholastic environment, where students share a plurality of differenttraining systems 102, so that each training system stores training dataat a common remote storage device. The ability of the present inventionto facilitate remote learning is significant. Instructor 110 can simplybe in a different room or building on a college campus, or can bethousands of miles away from where the students are located.

FIG. 12 is a flow diagram 99 that generally shows the logic for using amedical training system including contact-less sensors and correspondingdetection objects. As discussed above, such a medical training systemcan be implemented as a sensor bed and an exercise object, where sensorsare permanently or removably incorporated into the box trainer, andcorresponding detection objects are incorporated into the exerciseobject (which is preferably disposable). Such a medical training systemcan further alternatively be implemented as a medical model (such as thetorso including a simulated esophagus and simulated stomach, or asimulated knee, both of which have been described above), in which aspecific tool is used in connection with the medical model. Either thetool or the medical model will include one or more contact-less sensors,and the other of the tool or the medical model will include thecorresponding detection objects. Note in some embodiments, the toolitself comprises a detection object.

In a block 88, a medical training system including contact-less sensorsand corresponding detection objects is provided. In an optional block90, an instructor (or qualified practitioner, such as a surgeon or othermedical doctor) performs a baseline procedure using the medical trainingsystem. In an optional block 92, sensor data obtained when such askilled practitioner or instructor successfully completes a simulatedmedical procedure/training exercise are stored. Such sensor data can beused as a baseline for comparison to sensor data collected from anidentical simulated procedure/training exercise performed by a studentand used to evaluate student sensor data. For example, referring tomedical model 10 b of FIG. 4, a training exercise based on introducingan instrument into the stomach via the esophagus, and successfullylocating a stomach tumor can be implemented. The following three factorscan be used to evaluate such an exercise (it should be understood thatthe use of the following three factors is exemplary, rather thanlimiting on the scope of the present the invention): (1) the timerequired to negotiate the esophagus with the tool; (2) the time requiredto locate the tumor once the tool was advanced into the stomach; and,(3) whether the tumor was successfully located. Only sensor data fromthe student's exercise are required to determine if the tumor wassuccessfully identified. Sensor data obtained during a baselineprocedure are useful in providing a reference relating to the timerequired for a student to negotiate the esophagus with the tool, and areference relating to the time required for the student to locate thetumor. Based on the baseline procedure, the proctor or instructor candetermine that a student ought to able to perform these steps of theexercise, for example, in no more than twice the time required by theskilled practitioner. Thus, the sensor data obtained during the baselineprocedure can be compared with the sensor data from the studentexercise, to determine if the student meets the goal of performing thesame procedural steps in no more than twice the time required by theskilled practitioner. Obtaining baseline sensor data is not required,because even when timing data could be obtained from a baselineprocedure, a proctor or instructor could simply set timing goals basedon experience, rather than on sensor data derived from performing abaseline procedure.

In a block 94, a student performs a simulated medical procedure (or atraining exercise). If baseline sensor data have been collected, thestudent should perform an identical simulated medical procedure. In ablock 96, sensor data are collected during the student's performance ofthe procedure. In a block 98, feedback is provided, based on thecollected sensor data in comparison to the baseline sensor data.

The feedback provided is a function of how the processor is configuredto manipulate the sensor data received from the contact-less sensors. Inthe training exercise noted above with respect to a baseline procedurebeing performed by a skilled practitioner, the processor is configuredto provide feedback based on the following three factors: (1) the timerequired to negotiate the esophagus with the tool; (2) the time requiredto locate the tumor once the tool was advanced into the stomach; and,(3) whether the tumor was successfully located. Such feedback can beprovided to the student during the exercise, or kept hidden from thestudent until the exercise is complete, or can be sent to a proctor forgrading the student's performance. Based on the above-noted threefactors, a proctor may determine that the student's performance withrespect to all three factors must be acceptable in order to achieve apassing grade for the exercise, or the proctor may determine that apassing grade will be achieved as long as the tumor is located, and thatthe timing data will simply be provided to the student as feedback,rather than be used to determine if the student passed or failed theexercise. Those of ordinary skill in the art will recognize that sensordata can be used in many different ways to evaluate a student'sperformance.

In a simple form, contact-less sensors in accord with the presentinvention can be configured to provide feedback to a student during asimulated procedure. The data from the contact-less sensors can beutilized in a variety of different ways. For example, the data can beused to provide relatively simple feedback, such as turning lights on oroff, and/or activating aural or verbal prompts or cues. The data fromthe contact-less sensors can also be manipulated and analyzed by a morecomplex processing system, such as a computer. The use of a computerenables data collected during a training exercise to be immediatelyprocessed and displayed, immediately processed but stored for later use,stored for later processing, compared to similar data, electronicallydistributed to other users in a network, or any combination thereof.Where a student has previously performed the simulated procedure, theevaluation can include a comparison of the student's past performance incarrying out the procedure with the student's current performance. Thus,even if the student fails to achieve a passing score, the student mayreceive positive reinforcement of any improvement, based on a comparisonwith earlier attempts.

The concept of saving an old score and comparing the old score with acurrent score can be extended to include a comparison of a current scorewith the scores of other trainees. For example, a medical school maycollect data for students in each year of medical school who perform thesame simulated procedure. Those scores can be averaged to determine astandardized score for first year students, a standardized score forsecond year students, and so on. Trainees can then compare their scoreswith such standardized scores, to evaluate their progress. The scores ofother students can be further separated by class rank, so that traineescan evaluate their performance based on class rankings to see if theirscore is consistent with a higher class ranking or a lower classranking. Scores can also be collected nationally, so that trainees canevaluate their progress compared to a national average learning curve orother national statistics.

One score based metric that is likely to be very useful is a measurementof a rate at which skills are learned. Learning institutions that wishto increase the efficiency of their programs need to collect datarelating to different teaching strategies, in order to compare thedifferent strategies and identify those strategies that consistentlyresult in higher evaluation scores. Simulators including contact-lesssensors can be used to evaluate the performance of students undergoingdifferent training curriculums, and the results obtained can be comparedto identify the curriculum that leads to students receiving higherscores.

FIG. 13 schematically illustrates another type of feedback that might beprovided to a student using a trainer including contact-less sensors andcorresponding detection objects in accord with the present invention. Asshown in this Figure, a student is performing a training exercise usinga trainer 124, which includes one or more contact-less sensors (or oneor more detection objects). A processor 148 is coupled to the sensors(or detection objects, as described above) and is further coupled to adisplay 122. As discussed in detail above, the processor is configuredto provide feedback based on a signal received from at least one of thecontact-less sensors and the corresponding detection objects. Trainer124 is specifically configured to facilitate learning ultrasoundtechniques. Processor 148 is further logically coupled to a memory 150,and memory 150 includes a plurality of ultrasound images, such asultrasound image 126. As a student manipulates a simulated ultrasoundimaging probe 134, processor 148 will utilize the signals received fromthe contact-less sensors or the detection objects. As discussed indetail above, simulated ultrasound imaging probe 134 will include one ofa detection object or a contact-less sensor, while trainer 124 includesthe other of the detection object and the contact-less sensor.Significantly, simulated ultrasound imaging probe 134 can be implementedusing only a single detection object/contact-less sensor 146 (althoughadditional detection objects/contact-less sensors can be used), whereastrainer 124 will require a plurality of detection objects/contact-lesssensors, because trainer 124 functions by determining the position ofsimulated ultrasound imaging probe 134 relative to trainer 124, as thesimulated ultrasound imaging probe is moved over the surface of thetrainer and the student views ultrasound images of internal structures.As long as the position of simulated ultrasound imaging probe 134 can beaccurately determined relative to trainer 124, trainer 124 need notinclude any internal structures, and actual ultrasound images ofcorresponding internal structures of real patients can instead be used.That is, if the simulated ultrasound imaging probe is positionedrelative to the simulated torso so that an ultrasound image of thekidney would be obtained if the simulated torso were an actual patient,then the ultrasound image of a kidney of an actual patient (previouslyobtained) will be displayed to the student.

As shown in FIG. 13, trainer 124 comprises a simulated torso, includingsimulated kidneys 132. The simulated kidneys are disposed inanatomically correct positions relative to the simulated torso. Kidneys132 are indicated by dash lines because the kidneys will be hidden fromview by a layer of simulated tissue 130. The exact size and shape ofsimulated tissue 130 is not significant, so long as the simulated tissuecovers kidneys 132. Preferably, the size and shape of trainer 124 aresubstantially proportional to those of a fully-grown average male torso.However, in another embodiment, trainer 124 is alternatively formedaccording to the size and the proportions of a fully-grown averagefemale. In addition, in yet another embodiment, the trainer has the sizeand the proportions of a small child or infant. Trainer 124 rests on abase 125, which is preferably contoured to accommodate the trainer'sdimensions. In addition, trainer 124 is buttressed by underlyingstructures, giving realistic shape and appearance to the trainer asthough a complete muscular and skeletal system supports an exterior bodycover 123. A lower boundary 127 of the trainer is roughly commensuratewith the lower abdomen of an actual male. Parts of the hypogastric andiliac areas have been included, but the lower extremities have beenomitted. From the lower abdomen, the trainer continues to follow theoutline of an average-sized male torso. Lumbar and hypochondriac, medialand lateral areas, as well as umbilical and epigastric areas, arefaithfully replicated. Trainer 124 extends through the upper chest,which includes the upper neck portion. Upper extremities have beenomitted.

Preferably, simulated ultrasound imaging probe 134 will have a size,shape, and weight corresponding to an actual commercially availableultrasound imaging probe. If simulated ultrasound imaging probe 134includes a sensor (and trainer 124 includes a plurality of detectionobjects), then the sensor in simulated ultrasound imaging probe 134 willbe logically coupled to processor 148. If simulated ultrasound imagingprobe 134 includes a detection object (and trainer 124 includes aplurality of sensors), then the plurality of sensors implemented intrainer 124 will be logically coupled to processor 148. To enhance aresolution (i.e., to enhance the ability of trainer 124/processor 148 toaccurately determine the physical position of simulated ultrasoundimaging probe 134 relative to trainer 124), it may be useful to includean additional detection object/sensor in simulated ultrasound imagingprobe 134, at a position spaced apart from the first detectionobject/sensor in simulated ultrasound imaging probe 134.

Regardless of whether detection objects or sensors are implemented intrainer 124 (the other of the detection objects and sensors beingimplemented in simulated ultrasound imaging probe 134), the detectionobjects, the contact-less sensors, and the processor are configured tobe able to determine a position of simulated ultrasound imaging probe134 relative to simulated tissue 130 (and simulated kidneys 132). Thus,processor 148 can use an appropriate ultrasound image to display to thestudent. As the student moves simulated ultrasound imaging probe 134relative to simulated kidneys 132, a different ultrasound image will bedisplayed to the student.

The kidney displayed in ultrasound image 126 includes abnormal tissue128. Preferably, ultrasound image 126 will be an actual ultrasound imageof the kidney that includes actual abnormal tissue. However, ultrasoundimage 126 can also be implemented by taking an actual ultrasound imageof a healthy kidney and modifying the image to include a simulatedportion of abnormal tissue. Depending on the training scenario beingimplemented using trainer 124, each ultrasound image displayed to thestudent can be an ultrasound image of a healthy kidney, an ultrasoundimage of a diseased kidney, or combinations of ultrasound images ofhealthy kidneys and diseased kidneys (for example, the right simulatedkidney could simulate a healthy kidney, and the left simulated kidneycould simulate a diseased kidney). It should be understood that trainer124 can include additional organs, or different organs, so thatultrasound images of other organs are displayed to the student based onthe position of simulated ultrasound imaging probe 134 relative totrainer 124. Thus, an ultrasound trainer in accord with the presentinvention including a simulated kidney is intended to be exemplary,rather than limiting on the scope of the present invention.

In at least one embodiment, trainer 124 includes a sensor field of Halleffect or similar sensors incorporated into (or disposed beneath)simulated tissue 130, such that the sensor field is hidden from theuser's view. Each sensor in the sensor field is logically coupled toprocessor 148, so that each sensor sends a signal to the processor whensensing the detection object (a magnet when the sensor field comprisesmagnetic sensors) incorporated into simulated ultrasound imaging probe134. The processor is configured to process signals received from thesensor field, to determine the position of simulated ultrasound imagingprobe 134 relative to the sensor field incorporated into trainer 124.Based on the position of simulated ultrasound imaging probe 134, theprocessor is further configured to select an appropriate ultrasoundimage from memory 150. As the position of simulated ultrasound imagingprobe 134 changes relative to trainer 124 (i.e., as the studentmanipulates simulated ultrasound imaging probe 134), the processor willreceive updated sensor data from the sensor field, and a new ultrasoundimage may be selected, as appropriate.

Simulated tissue 130 will include a plurality of individuallyidentifiable detection objects or contact-less sensors (generallyconsistent with the principles discussed above in detail) such that theposition of simulated ultrasound imaging probe 134 relative to simulatedtissue 130 can be determined with a relatively high resolution. Thishigh resolution of the position will enable processor 148 to determinean appropriate ultrasound image to display to the student, based on theposition of the simulated ultrasound imaging probe relative to thetrainer. The greater the resolution provided, the more sensitive thetraining system will be to movements of the ultrasound imaging probe,and the more realistic the training simulation will be.

Simulated tissue 130 is preferably implemented as a plurality ofdifferent layers. In some embodiments of the invention, simulated tissue130 is incisable, such that a student can use a scalpel or othersurgical instrument to penetrate to the simulated tissue, to gain accessto simulated kidneys 132. Alternates to the preferred embodiment mayhave more or fewer layers, to simulate the different anatomical featuresfor a given area of the human body.

Where an incisable simulated tissue is employed, trainer 124 can be usedfor both ultrasound training and surgical training. It should beunderstood that the use of an incisable tissue to facilitate surgicaltraining is optional and not required. In embodiments includingincisable tissue, the trainer has swatches of simulated human tissuestructure draped over practice surgery areas and over areas of bodycover 123, and these swatches are preferably fastened to trainer 124with hook and loop fasteners or snap fasteners (not shown). Theincisable simulated tissue is intended to be replaced after its usefullife is expended. Only the practice surgical swatches need be replacedinstead of the entirety of body cover 123. Because body cover 123 is notintended to be incised, body cover 123 can be coupled to a rigid plasticbase. Preferably, the practice surgery areas include the abdomen, thechest, and the neck areas. Each of the practice areas may includefurther simulated anatomical features and more tissue structure, asdescribed below.

If trainer 124 is not intended for surgical training as well asultrasound training, a simpler simulated human tissue (including only askin layer and a detection object/sensor layer) can be employed, asdiscussed below. Simulated human tissue 130 preferably includes a numberof layers of elastomeric compositions selected and configured toreplicate the actual layered membranes and sub-membranes of a humanbody. The layers may be of similar formulation or they may be ofdifferent formulations, depending on the human tissue being simulated.For instance, simulated fat is of a different consistency than simulatedmuscle. As used herein, a stratum, or layer is used to denote asubstantially uniform area extending generally parallel to the outersurface. Layers in the human tissue structure may be bonded to oneanother, or they may be individual layers that are placed atop oneanother without being bonded. Layers may even be separated by membersthat are not a part of the human tissue structure. Further, for anygiven surgical area, the layers of simulated tissue 130 can vary inthickness.

Beginning with the uppermost and outermost layer, a composite skin layer136 simulates human skin. For the purposes of this description, skin isconsidered a membranous layer. Composite skin layer 136 includes anelastomeric layer 136 a and a fibrous layer 136 b. Elastomeric layer 136a is preferably implemented using a silicone blend, which can bepigmented to generally achieve a flesh tone. As is known in theelastomeric arts, any of a number of suitable pigments for coloringsilicone blends can be used to visually represent different layers. Thesilicone used in the invention is preferably obtained from Silicones,Inc. of High Point, N.C., and is sold under the trademark XP-153A™.Preferably, the silicone is mixed with a thinning agent, also obtainedfrom Silicones, Inc., and sold under the trademark GI THINNER™. Thevolume ratio of silicone to thinner may be adjusted to achieve asuitable hardness and texture, but preferably, the volume ratio isbetween about 2:1 and about 10:1 of silicone to thinner. Techniques formolding and curing items of silicone and thinner are known by those ofordinary skill in the art and need not be set forth herein to enable thepresent invention. Although silicone has been found to perform best,other elastomeric materials, such as latex, may alternatively be used.

It should be noted that attaching a fibrous layer to a silicone-basedsimulated skin layer requires care. In general, it is difficult to get anon-silicone material to bond to a silicone material. One method ofcoupling a fibrous layer to a silicone-based simulated skin layerinvolves coating the fibrous substrate with a silicone material. Such asilicone-coated fibrous layer substrate can be coupled to asilicone-based skin layer using a silicone compatible (preferably asilicone-based) adhesive. The fibrous layer is used because compositelayer 136 represents a membranous layer. Thus, a reinforcing layer iscombined with the elastomeric layer to enhance the realism of the skinlayer.

For the purposes of this description, human tissue, not including boneor cartilage, may be divided into two classes. The first class is tissuewhose presence in a human body fills or lends significant bulk. Thesecond class is tissue whose function is to line, support, or surroundthe first class of tissue. As used herein, the second class of tissue isthus referred to as a “membrane” or “membranes,” or as “membranoustissue.” By implication, the first class is referred to as“sub-membranous tissue.” Membranes are generally thinner, but arecharacterized in that they are comparatively more dense and tougher (todissect) than sub-membranous tissue, due in part to their compositeconstruction, since they typically include a fibrous layer. The types ofmembranes found in a human body include skin, serous membranes (such asthe peritoneum, pericardium, or parietal pleura), and any of a number offasciae or connective tissues, such as the deep fascia, which bindsmuscles (including the anterior and posterior rectus sheath oraponeuroses, ligaments, and tendons). By comparison, sub-membranoustissue, such as fat, muscle, or extraperitoneal tissue, occupies morespace and is generally easier to dissect than membranes. However, evenin the different tissues that are sub-membranous, there can be a greatdisparity in tissue consistency. For instance, fat is much easier todissect and has a very different tactile characteristic than muscle. Insome instances, the blunt end of a scalpel can be employed to readilydissect fat. Given the need to provide realistic simulation and trainingmodels, it is therefore appropriate to impart a level of realism tosurgical trainers that enables a user to experience the subtledifferences between membranous and sub-membranous tissues, as well as toexperience the tactile and visual characteristics of various types ofeach.

The substrate used in fibrous layer 136 b imparts a realistic resistanceto cutting, similar to the resistance of real human skin. The substrateis preferably made of a nylon mesh material. However, other fabrics thatperform equally well can alternatively be used. Any number of syntheticand natural fabrics are effective for use in this layer. While compositeskin layer 136 is intended to be a very close approximation to actualhuman skin, it is to be recognized that real human skin includesnumerous strata of virtually imperceptible differences. However,composite skin layer 136 of the present invention closely represents theepidermis and dermis of actual human skin. Preferably, a pigment isadded in the silicone blend to color the skin similar to human skin sothat as the skin layer is dissected, the color of the elastomericmaterial is suggestive of human tissue. Composite skin layer 136 ispreferably about 2 millimeters to about 4 millimeters thick. While apreferred embodiment of composite skin layer 136 includes a singlereinforcing fibrous layer 136 b, other embodiments can utilizeadditional reinforcing layers.

Sensor layer 140 of simulated tissue 130 is the layer including thenetwork of detection objects/sensors (i.e., the sensor field discussedabove). As noted above, the more detection objects/sensors included insensor layer 140, the more responsive to the training system will be tomovements of the simulated ultrasound imaging probe. Relatively fewdetection objects/sensors would mean that a student would need to movethe simulated ultrasound imaging probe a greater distance in order forprocessor 148 to display an additional ultrasound image to the student,compared to a sensor layer 140 that includes a greater number ofdetection objects/sensors. Suitable technology for implementingdetection objects/sensors has been discussed in detail above.

Underlying composite skin layer 136 and sensor layer 140 is a layer 142that simulates the subcutaneous fat found in actual human tissue. Forpurposes of this description, subcutaneous fat is considered asub-membranous layer. Subcutaneous fat layer 142 is preferably formed ofa silicone blend and includes a pigment. However, to simulate the lessdense texture of fat, the formulation is adjusted to be different thanthat used for the layer simulating skin. The volume ratios used for thefat layer are preferably in the range from about 1:1 to about 2:1,silicone to thinner. Subcutaneous fat layer 142 is similar in textureand hardness (tactile sensation) to a layer of subcutaneous fat found inhumans. In humans, the subcutaneous fat occurs as a thin layer of loosefatty tissue underlying the skin and binding it to underlying layers. Itis optional to provide a fibrous material or fibrous layer in thesubcutaneous fat and to add pigments. Preferably, subcutaneous fat layer142 is from about 10 to about 60 mm thick. It will be appreciated,therefore, that the relative thicknesses of layers in simulated humantissue 130 are not drawn to scale.

Underlying subcutaneous fat layer 142 is a composite layer representingan anterior rectus sheath layer 144. For purposes of this description,the anterior rectus sheath is considered a membranous layer. Theanterior rectus sheath layer includes an elastomeric layer 144 a(preferably a silicone blend) and a reinforcing silicone-coated fibrouslayer 144 b. Preferably, the fibrous material is a nylon mesh; however,SPANDEX™ material has also been found to perform well for this layer.Fibrous layer 144 b is pre-formed and bonded to elastomeric layer 144 ausing the method described above. Elastomeric layer 144 a can instead beprovided as a non-bonded layer. The formulation of silicone and thinnerused to form anterior rectus sheath layer 144 is preferably in the rangefrom about 1:0 to about 2:1, silicone to thinner. Silicone alone (withno thinner) may be used for this layer because the rectus sheath is adense, tough serous layer, and these characteristics can be achieved byusing little or none of the thinner.

Preferably, the silicone used for elastomeric layer 144 a is of adifferent consistency than that used for composite skin layer 136 orsubcutaneous fat layer 142. The silicone preferably used for producinganterior rectus sheath layer 144 is obtained from Silicones, Inc. underthe trademark GI-1000A™. This formulation of silicone is of a higherspecific gravity, and therefore, upon curing, will be denser thancomposite skin layer 136 or subcutaneous fat layer 142. For the sake ofcomparison, the lighter silicone, XP-153A™, has a specific gravity ofabout 0.98, while the more dense silicone, GI-1000A™, has a specificgravity of about 0.99. Preferably, anterior rectus sheath layer 144 isfrom about 0.5 to about 1.5 mm thick, and more preferably, about 1.0 mmthick. While a preferred embodiment of anterior rectus sheath layer 144includes a single reinforcing silicone-coated fibrous layer 144 b,additional reinforcing layers can be used. If desired, simulated tissue130 can include additional underlying layers, such as a muscle layer andadditional membranous layers (neither shown).

Note that the relatively complicated simulated tissue 130 is intended toprovide a realistic training experience when a student physicallymanipulates the simulated tissue, such as in a simulated procedure wherethe student is required to perform an incision and remove a simulatedkidney. In embodiments where simulated tissue 130 will be incised, thesimulated tissue is a consumable item that is intended to be readilyreplaced.

In other aspects of the present invention, simulated tissue 130 simplyprevents the contact-less sensors/detection objects associated with theskin layer from being visible to the student. In such an embodiment,simulated tissue 130 can be implemented using a single elastomeric layerand a sensor/detection object layer. While FIG. 13 indicates thatsimulated kidneys 132 are actually disposed beneath the simulated tissue130, it should be understood that particularly in embodiments wherephysical access to the simulated kidneys is not required, the simulatedkidneys can be omitted altogether (since it is the detection/sensorlayer that is responding to the position of the simulated ultrasoundimaging probe, not the simulated kidneys themselves). Thus, unlessaccess to the simulated kidneys is part of training scenarios to beimplemented using trainer 124, the simulated kidneys can be omitted, solong as processor 148 is programmed to recognize the individualsensors/detection elements in sensor layer 140 that correspond to ahypothetical position for the simulated kidneys.

Such an ultrasound trainer will enable students to gain familiarity withobtaining and reading ultrasound images, and to learn how themanipulation of ultrasound imaging probe relative to a patient willresult in the collection of different types of ultrasound images. Inearly training stages, a student may simply be instructed to obtain anultrasound image of the kidney. Trainer 124 will enable a student topractice positioning an ultrasound imaging probe relative to a patient(i.e., relative to the torso portion of trainer 124) until the simulatedultrasound imaging probe is properly disposed to obtain an ultrasoundimage of the kidney. The student can perform this training exercisewithout requiring an actual patient to be present, and if the ultrasoundimages have been previously generated by ultrasound imaging of realpatients, the student will be able to gain familiarity with actualultrasound images. In this basic training scenario, it is likely thatthe ultrasound images (stored in memory 150) of the kidney selected bythe processor for display will correspond to healthy kidneys. In moreadvanced training scenarios, ultrasound images from a patient having adisease condition relating to the kidneys can be obtained, and stored inmemory 150. A training exercise can be constructed using such images inwhich a student's ability to recognize the disease condition is tested.Significantly, the basic training exercise and the more advancedtraining exercise are performed on the same trainer. The only changethat needs to be made is to instruct processor 148 to display ultrasoundimages of normal kidneys, or ultrasound images from diseased kidneys.All of those images can be stored in memory 150. At the beginning of thetraining exercise, a menu may be displayed to the student such that thestudent can select an advanced or basic training exercise, and so thatthe images selected by the processor in response to the student'smanipulation of the simulated ultrasound probe will correspond to eitherthe advanced training scenario (the presence of a disease condition inthe kidneys) or the basic training scenario. Significantly, inultrasound training exercises involving live patients, a patient havinga kidney disease condition must be available in order for a student toobtain familiarity with visualizing disease conditions in ultrasoundimage during a training exercise. Using the present invention, a studentcan practice visualizing both healthy kidneys and diseased kidneys usingthe same trainer, without the need for any live patient to be available.

With respect to potential disease conditions of the kidney, cancer ofthe kidney is one of the more common kidney disease conditions. Renalcell carcinoma is the most common type of kidney cancer, accounting formore than 90% of malignant kidney tumors. Although renal cell carcinomausually grows as a single mass within the kidney, a kidney may containmore than one tumor. Memory 150 can store ultrasound images from severaldifferent patients having diseased kidneys, thereby enabling trainer 124to display a wide variety of different tumor sizes and locations. Inactual patients, a disease condition can affect both kidneys at the sametime. In a training exercise implemented using trainer 124, processor148 can be configured to simulate a patient having a disease conditionpresent in only one kidney, or in both kidneys.

The present invention can be implemented as a system that collects datausing contact-less sensors that are incorporated into a simulatedphysiological structure (or a simulated tool used to manipulate thesimulated physiological structure, or a sensor bed, as discussed indetail above), stores the collected data in a digital format, processesand evaluates the data, and compares the data to related data. Thebenefits of the present invention will thus be readily apparent from thediscussion presented above.

Although the present invention has been described in connection with thepreferred form of practicing it and modifications thereto, those ofordinary skill in the art will understand that many other modificationscan be made to the present invention within the scope of the claims thatfollow. Accordingly, it is not intended that the scope of the inventionin any way be limited by the above description, but instead bedetermined entirely by reference to the claims that follow.

1. A physiological training and evaluation simulator suitable fortraining and testing personnel, comprising: (a) a simulatedphysiological structure into which a detection target is incorporated;and (b) a sensor bed configured to support the simulated physiologicalstructure, the sensor bed including at least one contact-less sensorconfigured to respond to a proximity of the detection target during atraining simulation, wherein the detection target is embedded within aportion of the simulated physiological structure that is to be removedduring the training simulation, so that when the portion is successfullyremoved, the at least one contact-less sensor is no longer triggered bythe detection target, indicating that the training simulation has beensuccessfully performed with the removal of said portion.
 2. Thephysiological training and evaluation simulator of claim 1, wherein thedetection target is embedded in a way so that the detection target ishidden from view during a simulated procedure, such that a user cannotsee the detection object while the simulated physiological structure ismanipulated during a simulated procedure, the detection target beinghidden from view by a portion of the simulated physiological structuredisposed proximate the detection object.
 3. The physiological trainingand evaluation simulator of claim 1, wherein the sensor bed isincorporated in a box trainer, and the simulated physiological structureis disposed within a working volume in the box trainer.
 4. Thephysiological training and evaluation simulator of claim 1, wherein theat least one contact-less sensor comprises at least one sensor selectedfrom the group consisting of an inductive sensor, an eddy-currentsensor, a capacitance sensor, and an impedance sensor.
 5. Thephysiological training and evaluation simulator of claim 1, wherein theat least one contact-less sensor comprises a plurality of analogcontact-less sensors distributed throughout the physiological trainingand evaluation simulator, so that by monitoring the plurality of analogcontact-less sensors, a processor determines a three-dimensionallocation of the detection target during the training simulation.
 6. Thephysiological training and evaluation simulator of claim 1, wherein thedetection target comprises a radiofrequency identification (RFID) tag,and the at least one contact-less sensor comprises an RFID tag reader.7. A medical training simulator suitable for training and testingpersonnel, comprising: (a) a contact-less sensor; (b) a detection objectadapted to trigger the contact-less sensor; (c) a simulatedphysiological structure configured to visually and tactilely resemble ananatomical structure; and (d) a sensor bed configured to support thesimulated physiological structure, the detection object beingincorporated into one of either the sensor bed or the simulatedphysiological structure, and the contact-less sensor being incorporatedinto the other of the sensor bed and the simulated physiologicalstructure, such that the one of the detection object and thecontact-less sensor incorporated into the simulated physiologicalstructure is embedded within a portion of the simulated physiologicalstructure that is to be removed during the training simulation, so thatwhen the portion is successfully removed, the contact-less sensor is nolonger triggered by the detection target, indicating that the trainingsimulation has been successfully performed with the removal of saidportion.
 8. The medical training simulator of claim 7, wherein thedetection object comprises a radiofrequency identification (RFID) tag,and the contact-less sensor comprises an RFID tag reader.
 9. The medicaltraining simulator of claim 8, wherein the RFID tag is embedded in thesimulated physiological structure.
 10. A method for evaluating aperformance of a simulated medical procedure, comprising the steps of:(a) performing the simulated medical procedure, wherein properperformance of the simulated medical procedure requires removing aportion of a simulated physiological structure from a balance of thesimulated physiological structure, such that one of either acontact-less sensor or a detection object is moved relative to the otherof the contact-less sensor and the detection object, the contact-lesssensor producing sensor data during the simulated medical procedure inresponse to the detection object and the portion being removed isconfigured to resemble an anatomical structure; (b) collecting thesensor data during the performance of the simulated medical procedure,wherein the sensor data are collected without requiring physical contactbetween the contact-less sensor and the detection object; and (c) usingthe sensor data to evaluate the performance of the simulated medicalprocedure, including the step of determining if the portion of thesimulated physiological structure removed contained one of thecontact-less sensor and the detection object, and if so, concluding thatthe simulated medical procedure was performed correctly.
 11. The methodof claim 10, wherein the step of using the sensor data to evaluate theperformance of the simulated medical procedure comprises the step ofcomparing the sensor data obtained during the simulated medicalprocedure with sensor data obtained from a baseline procedure, in orderto evaluate the performance of the simulated medical procedure.
 12. Themethod of claim 10, wherein the step of collecting sensor data duringthe performance of the simulated medical procedure comprises the step ofcollecting the sensor data based on at least one of: a capacitance, animpedance, a magnetic field, and an inductance.
 13. The method of claim10, wherein the detection object comprises a radiofrequencyidentification (RFID) tag, and the contact-less sensor comprises an RFIDtag reader.
 14. A physiological training and evaluation simulatorsuitable for training and testing personnel, comprising a simulatedphysiological structure including a simulated esophagus, the simulatedesophagus including a simulated stricture, the simulated stricturecomprising a sensor, the sensor being configured to determine if thesimulated structure is properly dilated during a simulated medicalprocedure.
 15. The physiological training and evaluation simulator ofclaim 14, wherein the simulated stricture further comprises a firstfluid chamber, a second fluid chamber, and a valve disposed between thefirst fluid chamber and the second fluid chamber, such that when thesimulated stricture is properly dilated during the simulated medicalprocedure, a fluid moves from the first fluid chamber into the secondfluid chamber.
 16. The physiological training and evaluation simulatorof claim 14, wherein the simulated stricture further comprises adetection object, and the sensor comprises a contact-less sensor.
 17. Amedical trainer for teaching and testing personnel, comprising: (a) asimulated physiological structure, a portion of the simulatedphysiological structure being configured to be removed during theperformance of a simulated procedure, the simulated physiologicalstructure comprising an elastomer and being configured to simulate ananatomical structure, the simulated physiological structure beingdisposed within a working volume defined by the physiological trainingand evaluation simulator; (b) a detection object; and (c) a contact-lesssensor configured to respond to a proximity of the detection object, oneof either the detection object or the contact-less sensor being disposedin the portion of the simulated physiological structure, and the otherof the detection object and the contact-less sensor being disposedadjacent to the portion of the simulated physiological structure, suchthat removal of the portion of the simulated physiological structureduring the simulated procedure is detected, because the detection objectis no longer detected by the contact-less sensor after the portion ofthe simulated physiological structure is removed, wherein thecontact-less sensor does not require physical contact between thecontact-less sensor and the detection object to detect the detectionobject.
 18. The medical trainer of claim 17, wherein the detectionobject comprises a radiofrequency identification (RFID) tag, and thecontact-less sensor comprises an RFID tag reader.